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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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“Spike Generation via Slow Network Integration and Fast Neural Integration in Awake Brain”
Annabelle Singer, Ph.D.*
Postdoctoral Fellow
McGovern Institute for Brain Research
Massachusetts Institute of Technology Media Lab
Seminar will be made available via videoconference in the Health Sciences Research Building, room E 160 and Technology Enterprise Park, room 104.
Neural codes have long been examined at the spiking level revealing how such activity, from single to hundreds of cells, relates to behavior. These codes are communicated through synaptic connections from one cell to another. Ultimately the significance of these codes, how they are decoded and propagated, depends on how neurons receive and respond to synaptic inputs. Extensive work in vitro on how neurons respond to synaptic inputs has focused on fast neural integration, in which neurons integrate subthreshold activity within a few milliseconds toward spike threshold. However little is known about this process in awake animals when both the biophysics of the cell and the patterns of inputs the cell receives are fundamentally different. In the awake brain, we have found that neurons consistently exhibit gradual rises in voltage, lasting up to hundreds of milliseconds, before fast rises in voltage that precede spikes. Indeed, fast rises rarely yield spikes unless they are preceded by a gradual rise, and spike occurrences can be predicted to some extent from the amplitude and duration of the gradual rise alone. These slow rises precede spikes in neurons of multiple brain regions of awake mice, the cortex as well as the hippocampus, and in multiple network and behavioral states, revealing a degree of generality to these findings. Recordings using a multiple-neuron version of our automatic patch clamp robot show that these gradual rises are often coordinated across nearby cells, whereas fast rises are cell-specific. This suggests that slower, network-level integration interacts with faster, classical integration within single neurons to generate spike patterns. In this way network activity, perhaps population codes that occur over tens to hundreds of milliseconds, may gate whether subsequent cell-specific inputs result in a spike. In future work, we will further develop this in vivo robotic approach and elucidate fundamental mechanisms of awake brain computation and their role in behavior and disease.
Faculty Host: Lena Ting, Ph.D.
